Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
16,761 documents
The strategy applies a long-only moving average crossover to daily bars for a single stock. After enough bars are available to calculate both averages, it treats an upward cross of the shorter average over the longer one as an entry signal and buys when…
The document describes a graphical workflow for downloading historical bars, configuring a CTA strategy backtest, reviewing performance statistics, and inspecting trades on a candlestick chart. Data can come from a domestic market data service, an…
The document walks through preparing a Python environment, installing a trading framework, and launching its graphical interface. The example registers exchange gateways and applications for strategy execution, historical data recording, risk controls,…
The document explains a local simulator that routes orders and cancellations to a paper-trading engine instead of sending them to an external trading server. It supports limit, market, and stop orders, and uses quote-triggered matching: for example, a buy…
This document describes a framework for building trading strategies around market-data and order-event callbacks. A strategy can receive tick, bar, trade, order, and stop-order updates; load historical bars or ticks during initialization; and query or…
This guide explains a workflow for researching CTA strategies with historical market data. It covers obtaining and storing data, configuring a backtest with a strategy, date range, slippage, fees, contract multiplier, tick size, and starting capital, then…
This document describes a charting utility for displaying market candles and volume alongside technical indicators. It organizes the view into a main price panel, a volume panel, and a secondary indicator panel, and includes a line for the latest traded…
This document describes the data model and calculations behind a synthetic multi-leg spread. Each leg stores its market quotes, contract details, and position state. Configurable price multipliers define the spread price, while trading multipliers define how…
The document presents a workflow for evaluating individual trades from a Turtle-style strategy backtest on an hourly Bitcoin instrument. It configures a backtest with a historical date range, fees, slippage, contract size, tick size, and starting capital,…
This strategy combines Bollinger-style price bands with the Commodity Channel Index (CCI) to generate directional entries on 15-minute bars. It calculates a simple moving average and standard deviation over a configurable lookback, then places a stop entry…
This spot strategy generates signals from a fast and a slow moving average. It identifies a bullish crossover using completed bar values rather than the current bar, which is intended to avoid signals that flicker while a bar is forming. A bullish cross…
This strategy uses Bollinger-style price bands to enter long or short positions when a bar reaches beyond the upper or lower band. It adds a directional filter based on the difference between the latest close and a close from an earlier lookback: positive…
This guide explains a market-data recorder that subscribes to selected instruments and saves live tick or one-minute bar data to a database. The stored history can then be reviewed in a data-management interface, used in historical backtests, or loaded to…
This example shows a workflow for backtesting an ATR-RSI strategy on one-minute futures data. The setup specifies the contract, date range, transaction costs, slippage, contract size, tick size, and starting capital, then loads data, runs the simulation,…
This example describes a directional strategy that uses two exponential moving averages on hourly bars. It compares a 15-period average with a 50-period average and treats a crossover between the latest and prior readings as a change in direction. When flat,…
This document contains daily open, high, low, close, and volume observations for Bitcoin priced in USDT during 2020. The rows are timestamped at 08:00 and show the market's changing price and trading volume through the year. The visible records include sharp…
This analysis workflow loads historical bars into a time-indexed table and plots closing prices to inspect gaps. It applies a Ljung–Box test for randomness, an Augmented Dickey–Fuller test for stationarity, and autocorrelation plots to examine serial…
This overview maps a CTA trading system into components for strategy templates, example strategies, backtesting, order conversion, live execution, and a graphical interface. It describes how live initialization can retrieve historical bars through a data…
The document presents a bar-by-bar backtest using historical price data loaded from a CSV file. As each bar is added, the strategy calculates 20-period and 30-period moving averages after sufficient history is available. It enters a long position when the…
The document describes a long and short strategy driven by fast and slow moving averages. It checks crossover conditions using completed-bar values, then opens a position or reverses an existing one. Position size is calculated from current account assets,…
The document explains a graphical workflow for maintaining historical market data. Users can download data from connected market data services or trading interfaces, import CSV files, inspect stored records, export selected ranges, and delete contract data.…
The document surveys the components of a Python trading framework, from connections to market venues through strategy development and automated execution. It outlines event-driven infrastructure, data handling, graphical tools, and applications for…
The document shows a workflow for backtesting two strategies on different cryptocurrency markets, then adding their result data frames to form a combined portfolio series. A helper configures each run with market, interval, date range, transaction costs,…
This analysis workflow loads historical bars into a tabular dataset and plots closing prices to inspect gaps. It applies a Ljung–Box test for serial dependence, an augmented Dickey–Fuller test for stationarity, and autocorrelation and partial autocorrelation…